ABS Zaurion Duo Aqua
A Ready-to-Deploy Dual-GPU Workstation Powerhouse That Gives You a Stylish, Distraction-free workspace
Pioneer new frontiers in AI, data science, and graphics.
With Dual NVIDIA RTX PRO 6000 Blackwell Max-Q
Perfect for multi-GPU workloads like large-scale data modeling, distributed rendering, or multi-instance AI training and inference.
AI Development
Accelerate AI development and inference workloads, and build agentic AI applications.
Data Science
Accelerate your data pipelines.
AI-Driven Rendering and Graphics
Deliver stunningly realistic designs and simulations with speed and precision.
HPC
Accelerate scientific breakthroughs with enhanced accuracy.
Video Content and Streaming
Boost performance for live media and video pipelines.
Powered by NVIDIA Blackwell Architecture
Fifth-Gen Tensor Cores
Max AI performance with FP4 and DLSS 4
New Streaming Multiprocessors
Optimized for RTX Neural Shaders
Fourth-Gen Ray Tracing Cores
Built for RTX Mega Geometry
5th Gen Tensor Cores
Fifth-generation Tensor Cores deliver up to 3X the performance of the previous generation and add support for FP4 precision and DLSS 4 Multi Frame Generation technology. Accelerate local LLMs, prototype new AI models, and drive enhanced content creation and graphics.
4th Gen RT Cores
Fourth-generation RT Cores deliver up to 2X the performance of the previous generation, accelerating rendering for M&E content creation, AECO design, and manufacturing prototyping. Create photoreal, physically accurate scenes and immersive 3D designs with neural graphics-based technologies, such as RTX Mega Geometry, enabling up to 100X more ray-traced triangles.
CUDA Cores
NVIDIA Blackwell is the most powerful professional RTX GPU ever created with the latest SM and CUDA® core technology. The SM features increased processing throughput, and new neural shaders that integrate neural networks inside of programmable shaders to drive the next decade of AI-augmented graphics innovations.
96GB of GPU Memory
New and improved GDDR7 memory significantly boosts bandwidth and capacity, empowering your applications to run faster, and work with larger, more complex datasets. With 96GB of GPU memory, tackle massive 3D and AI projects, explore large-scale VR environments, and drive larger multi-app workflows.
9th-Gen NVENC
Ninth-generation NVIDIA NVENC engines significantly accelerate video encoding speed, and improve quality for professional video applications. They add new support for 4:2:2 H.264 and HEVC encoding, and improve HEVC and AV1 encoding quality.
6th-Gen NVDEC
Sixth-generation NVIDIA NVDEC engines provide up to double H.264 decoding throughput and offer support for 4:2:2 H.264 and HEVC decode. Professionals can benefit from high-quality video playback, accelerate video data ingestion, and use advanced AI-powered video editing features.
Multi-Instance GPU
Multi-Instance GPU (MIG) expands the performance and value of RTX PRO 6000 Max-Q by enabling the creation of up to four (4) fully isolated instances. Each MIG instance has its own high-bandwidth memory, cache, and compute cores. and guaranteed quality of service (QoS), extending the reach of accelerated computing resources to every user.
PCIe Gen 5
Support for PCI Express Gen 5 provides double the bandwidth of PCIe Gen 4, improving data-transfer speeds from CPU memory and unlocking faster performance for data-intensive tasks like AI, data science, and 3D modeling.
Max-Q
Packing a 300W punch into an ultra-efficient design, the RTX PRO 6000 Max-Q redefines high-density workstation performance. Optimized for energy and space efficiency, it enables up to 4 GPUs in a single system, delivering unmatched scalability for AI training, 3D rendering, and complex simulations.
Industry-Leading Performance
AI Performance
3511 TOPS1,2
RT Core Performance
333 TFLOPS1
Single-Precision Performance
110 TFLOPS1
Intel® Xeon® W-2400 Processors
Performance Workstation CPU
Intel® Xeon® w5-2455X Processor
30M Cache, 3.20 GHz
Intel® Xeon® w7-2495X Processor
45M Cache, 2.50 GHz
Expanded Compute Architecture
Alleviate processing bottlenecks with advanced CPU packaging technology featuring Embedded Multi-die Interconnect Bridge (EMIB) technology. This technology elegantly connects multiple heterogeneous dies in a single solution and enables up to 60 cores in a single socket.
Designed for AI Development
Data scientists and AI developers can experience up to 26% faster linear algebra performance3 thanks to built-in acceleration tools and world-class platform capabilities, which deliver high core counts, large cache sizes, high PCIe connectivity, and high memory capacity for a robust AI development platform.
Built for Business Stability
Enterprises can operate efficiently with a seamless, reliable, and secure system management experience backed by the peace of mind offered by a suite of professional-grade technologies, such as error correcting code (ECC) memory, reliability, availability, and serviceability (RAS) features, and support for select Intel vPro® Enterprise technology4.
Experience Unrivaled Performance with Intel® Xeon® W Series Processors
AI/Data Science, up to
26 %
faster linear algebra performance3
Engineering, up to
59 %
faster FEA simulation5
Media and entertainment, up to
2.4 x
faster rendering6
Professional Thermal Solution
Internal airflow diversion ensures performance and heat dissipation
Low Noise Performance Ensures Comfortable Working Space
Full GPU load performing under 50dB
Storage Support
Mix Drives
Plentiful NVMe and SATA Storage interface can fulfill your hot and cold data processing requirement at once.
- Onboard 2 x M.2 2280 slots (PCIe 4.0 x4) from PCH
- 4 x 3.5” / 2.5” SATA hot-swap HDD/SSD bays
- Optional 4 x 3.5” / 2.5” SATA hot-swap HDD/SSD bays
Connectivity
Dual Intel® 10GbE LAN
The Intel® X710-AT2 supports 2 x 10GbE configuration which is the foundation for workstation connectivity, providing broad interoperability, critical performance optimizations, and increased agility for Communications, Cloud, and Enterprise IT network solutions.
Optional AI Memory Optimization with Phison aiDAPTIV+
This system supports optional Phison aiDAPTIV+ SSD to significantly reduce GPU VRAM requirements for Full Fine-Tuning of large language models.
Key Message
With optional aiDAPTIV+, customers can fine-tune large LLMs using much smaller GPUs, dramatically lowering hardware cost and deployment complexity.
| Target Model Size | VRAM Needed (Without aiDAPTIV+) | VRAM Needed (With aiDAPTIV+) | Typical Hardware |
|---|---|---|---|
| = 13B | 120-200 GB | 32 GB | 1x RTX 5090 |
| = 34B | 250-350 GB | 96 GB | 1x RTX PRO 6000 |
| = 70B | 500-700GB | 192 GB | 2x RTX PRO 6000 |
What this means
- Without aiDAPTIV+, Full Fine-Tuning typically requires multi-GPU servers
- With optional aiDAPTIV+, the same model can be trained on a single workstation
- This enables lower cost, simpler deployment, and faster AI adoption
Phison aiDAPTIV+ SSD is optional add-on and is not included by default.
Product Overview
1. Peak rates based on GPU Boost Clock.
2. Theoretical FP4 TOPS using sparsity.
3. Based on NumPy/SciPy – iBench Python measurements on Intel® Xeon® w9-3595X versus AMD Threadripper Pro 7985WX processors, in NumPy/SciPy - ibench for Linear Algebra, geomean of performance increase across multiple algorithms. See www.intel.com/performanceindex for configuration details. Results may vary.
4. All versions of the Intel vPro® platform require an eligible Intel processor, a supported operating system, Intel® LAN and/or WLAN silicon, firmware enhancements, and other hardware and software necessary to deliver the manageability use cases, security features, system performance, and stability that define the platform. See intel.com/performance-vpro for details.
5. Based on Ansys Mechanical – Overall score results on Intel® Xeon® w7-2595X vs. Intel® Xeon® W-2295 processor. See www.intel.com/PerformanceIndex for workloads and configurations. Results may vary.
6. Based on Arnold Renderer in Autodesk 3DS Max score results on Intel® Xeon® w9-3595X vs. Intel® Xeon® W-3275 processor. See www.intel.com/PerformanceIndex for workloads and configurations. Results may vary.